Every method of diagnosis and prognosis depends upon some model or theory of disease. If the diagnosis or prognosis includes probabilities of disease characteristics (usually categorical) or degrees of involvement of various pathological processes, the problem of estimating the parameters inherently implies a definition of disease and/or disease processes. This project has as its specific objective the development of alternative models of disease, explicity aimed at quantification of the most important latent attributes characteristic of a disease syndrome. The aim is exploiting the growing medical data bases available in clinical and research information systems. This requires extension and refinement of statistical classification procedures, and is more consistent with medical theory which treats the patient and his disease as unique. One approach involves evaluating a disease state in terms of degrees of involvement in various alternative idealized syndromes. Preliminary experience indicates that disease structures estimated this way correspond closely to the clinical impressions of experienced physicians. In addition, this method quantifies such heretofore vague notions as "degree of sickness" and "degree of risk". Probabilities of outcomes for the individual patient can be synthesised by forming a combined probability from the grades of membership and the outcome probability for each. A second approach involves the definition of fundamental pathological processes for progressive diseases, and bears implications for the study of chronic disease and aging. A third approach will consider reversible disease processes so that acute illnesses can be dealt with.